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264 articles for “clinical applications”
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Advancements in Polymer Chemistry for Biomedical Applications: A Focus on Injection Guides
Abstract: Polymers have revolutionized biomedical applications, offering versatility, biocompatibility, and cost-effective manufacturing. This paper explores the role of polymer chemistry in the development of an advanced injection guide for precise drug delivery, aiming to enhance both safety and efficiency in clinical settings. Emphasis is placed on polymer selection, structural design, and functional modifications to improve injection procedures. By leveraging biodegradable and biocompatible polymers, the guide minimizes adverse tissue reactions while ensuring …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 129–136 Read article
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Recent Update on Advanced Drug Delivery System
Abstract: Over the past decade, there has been a growing interest in the use of artificial intelligence (AI) technology for analysing and interpreting biological or genetic data, accelerating drug discovery, and identifying selective small-molecule modulators or rare molecules in addition to predicting their behaviour. The use of artificial neural networks (ANNs) for the rapid analysis of massive amounts of data, the development of novel hypotheses and treatment plans, the prediction of …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 1, 2023 · pp. 22–30 Read article
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A Clinical Case Study of Kaphaja Visarpa W.S.R to Pemphigus Vulgaris
Abstract: Background: Visarpa is a classical Ayurvedic dermatological condition characterised by Swift spreading of lesions across the skin involving Twak, Lasika, Rakta, and Mamsa. Kaphaja Visarpa, a subtype dominated by Kapha dosha, presents with pallor-coloured oily lesions, itching, swelling, and mild pain. Case Summary: A 58-year-old female patient, a known case of Type 2 Diabetes Mellitus, presented with shiny, oedematous, pale skin lesions across the chest, abdomen, and back, accompanied by …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 2, 2026 Read article
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Skin Cancer Detection System Based on Machine Learning for Recognition of Cancerous Images
Abstract: Skin cancer ranks among the most prevalent types of cancer globally and poses significant risks when left untreated. Skin cancer arises when abnormal cells proliferate uncontrollably in the skin. This uncontrolled growth can be triggered by genetic mutations, exposure to ultraviolet (UV) radiation from the sun or artificial sources like tanning beds, or various other factors. In this, the early detection of cancer plays a crucial role in treatment and …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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Elderly Healthcare Using Federated Learning Approach
Abstract: The healthcare system for elderly people faces several challenges, which can be addressed using advanced machine learning models. These models can help monitor chronic diseases, detect falls, and provide personalized health recommendations. The study uses comprehensive datasets like MIMIC-III/IV, WESAD, and UCIHAR to explore human movements, device limitations, and the differences in fall occurrences. A detailed review of existing literature discusses current technologies for activity monitoring and fall detection, focusing …
Published in Current Trends in Information Technology · Vol. 16, Issue 1, 2025 · pp. 13–23 Read article
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Designing and Developing a Cancer Chatbot in a Website
Abstract: Cancer is a disease that affects millions of people worldwide each year and is characterized by the rapid growth of cells that are abnormal. The outcome is affected since numerous cases are discovered at advanced stages of the disease. Anxiety and depression are two mental health issues that frequently coexist with the illness, worsening its effects on sufferers. There were many medical apps that provide guidelines for patients, but these …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 1, 2024 · pp. 1–9 Read article
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An Open Labelled Parallel Arm Randomized Clinical Trial of Tuvaraka Oil Prepared By Two Different Method In The Management of Pama
Abstract: In Ayurveda, all skin diseases have classified mainly into two groups i.e., Mahakushtha (major skin diseases) and Kshudrakushtha (minor skin diseases). Tuvaraka [Hydnocarpus laurifolia (Dessnt).Sleumer] is one among the most useful drugs for the treatment of Kushtha (Various skin diseases) and Madhumeha (Diabetes Melitus). Pama is described under Kshudra Kushtha. which can be correlates with scabies. Aim: To evaluate the clinical efficacy of Tuvaraka oil prepared by modified method and …
Published in Research & Reviews : Journal of Herbal Science · Vol. 13, Issue 1, 2024 · pp. 29–36 Read article
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Artificial Intelligence in Drug Repurposing: A Short Impact Assessment
Abstract: Artificial intelligence (AI) in pharmaceutical repurposing has become a game-changing tool that opens new avenues for the application of new drugs that have already been approved. Traditional drug discovery is a lengthy and expensive process, whereas AI can rapidly analyze vast datasets of biological, chemical, and clinical information to predict drug-disease interactions. AI-driven techniques, such as machine learning, natural language processing, and deep learning, enable the identification of potential repurposing …
Published in Trends in Drug Delivery · Vol. 11, Issue 3, 2024 · pp. 42–45 Read article
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Role of Centella asiatica in Alzheimer’s Disease: A Comprehensive Review
Abstract: Alzheimer's disease (AD) is a progressive neurological illness that causes cognitive decline and memory loss and affects millions of people worldwide. As synthetic medications often prove ineffective or cause severe side effects, natural remedies are gaining attention. This review explores the potential of Centella asiatica, a herb traditionally used in oriental medicine, in the treatment of Alzheimer's disease. Triterpenoids, asiaticoside, and madecassoside are among the bioactive substances found in Centella …
Published in International Journal of Brain Sciences · Vol. 1, Issue 2, 2024 · pp. 1–7 Read article
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Evaluation of Small Vessel Disease by Advanced Brain Imaging
Abstract: Studying and comprehending brain small vessel disease requires extensive imaging. Recent applications of cutting-edge brain imaging techniques have led to the discovery of several significant results. Diffusion-weighted MRI studies have demonstrated the diagnostic accuracy of using clinical features alone or in combination with CT scan results to identify small vessel disease as the underlying cause is suboptimal in patients with acute lacunar syndromes. Acute infarcts caused by small vessel disease …
Published in International Journal of Cheminformatics · Vol. 2, Issue 1, 2024 · pp. 15–19 Read article
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An Insightful Study on SMEDDS Challenges and Potential Strategies
Abstract: Self-microemulsifying drug delivery systems (SMEDDS) have gained attention as an effective approach to enhance the bioavailability of poorly water-soluble drugs. They are innovative lipid-based formulations designed to enhance the solubility, bioavailability, and therapeutic efficacy of poorly water-soluble drugs. The development of SMEDDS involves systematic selection of components based on solubility and emulsification efficiency, followed by optimization of ratios using pseudo-ternary phase diagrams. The resulting formulations are evaluated for droplet size, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 311–334 Read article
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The Role of Gut Microbiota in the Health Effects of Fermented Dairy Products
Abstract: The human gut microbiota plays a crucial role in maintaining physiological health, influencing digestion, metabolism, immune function, and even mental well-being. Among dietary interventions aimed at modulating gut microbiota, fermented dairy products have emerged as particularly promising due to their rich content of live microorganisms, bioactive compounds, and nutrients. This review explores the intricate interactions between fermented dairy products and the gut microbiota, highlighting their potential health benefits and underlying …
Published in Research and Reviews : Journal of Dairy Science and Technology · Vol. 14, Issue 2, 2025 · pp. 5–10 Read article
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Accelerating Drug Discovery with AI: Transforming the Pharmaceutical Pipeline
Abstract: The revolutionary potential of artificial intelligence (AI) is examined in this essay the pharmaceutical industry, highlighting its application across the drug development lifecycle. Artificial Intelligence, specifically via deep learning models and machine learning (ML) such as GANs, RNNs, and transformers, enhances drug discovery, formulation, toxicity prediction, and clinical trials. It streamlines processes like identification of targets, virtual screening, modelling of structure-activity relationships, and medication repurposing. AI is also employed in …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 77–84 Read article
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Comprehensive Review of Adenoid Cystic Carcinoma: Pathogenesis, Diagnosis, and Emerging Therapeutic Approaches
Abstract: Adenoid cystic carcinoma (ACC)is an infrequent neoplasm, highly malignant, that develops mainly in the salivary glands with the potential to exist in any secretory glandular sites, including the lacrimal glands, breast, and respiratory tract. ACC usually has a benign initial course, but conversely, it is notoriously aggressive in behavior with high incidence of perineural invasion, local recurrence, and distant metastasis, mostly to the lungs. The tumor’s molecular features are characterized …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 3, 2025 · pp. 1–17 Read article
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Disease Prediction Using Ensemble Learning Models: A Comprehensive Approach
Abstract: In recent years, ensemble learning techniques have become pivotal in advancing predictive analytics within healthcare, particularly for early disease detection. The inherent variability and complexity of medical data, often characterized by high dimensionality, class imbalance, and noise, make it challenging for standalone classifiers to maintain high predictive accuracy. Ensemble learning, by integrating multiple models through bagging, boosting, or stacking, offers a more robust and generalizable approach. This study explores the …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 3, 2025 · pp. 26–33 Read article
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SIBR/Aloe barbadenis Mill.: A Review on Medicinal Utility from the Perspective of Unani Medicine
Abstract: Aloe barbadensis Mill., known as Sibr in Unani medicine, is a time-honored medicinal plant belonging to the family Liliaceae. Revered across cultures and healing systems, it has been extensively described in Unani literature under various names such as Elwa, Musabbar, and Ghikwar. This review aims to comprehensively explore the medicinal utility of Sibr from an Unani perspective while integrating evidence from modern pharmacognosy, phytochemistry, and pharmacology. Traditionally, the dried juice …
Published in Research & Reviews : A Journal of Unani, Siddha and Homeopathy · Vol. 12, Issue 3, 2025 · pp. 22–29 Read article
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The Mycobiome Frontier – Pre & Post 2020 Status: Integrating Fungal Bioactive Compounds, Probiotics, and Antimicrobial Peptides in Modern Therapeutics and Biotechnology.
Abstract: The fungal kingdom represents an indispensable resource in modern therapeutics and biotechnology, offering a diverse array of bioactive compounds, probiotics, and antimicrobial peptides (AMPs). Functional fungal polysaccharides (FFPs), such as beta-glucans, chitin, and mannans, are centrally involved in modulating the human gut microbiota, providing novel therapeutic avenues for chronic conditions including diabetes, neurodegenerative disorders, and cancer. These compounds act as prebiotics, nourishing beneficial bacteria and enhancing metabolic parameters such as …
Published in International Journal of Fungi · Vol. 3, Issue 1, 2026 · pp. 1–11 Read article
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Carboxymethyl Cellulose-Based Spray-Dried Microspheres: Recent Advances and Applications in Targeted Drug Delivery Systems
Abstract: Microspheres are spherical particles ranging from 1 to 1000 μm, made from natural or synthetic polymers and inorganic materials. Their structure allows precise drug delivery, improving targeted release and minimizing off-target effects. Natural polymers such as starch, chitosan, and alginate are favored for their biodegradability, adhesion, and compatibility, enhancing mucosal interaction and residence time. Microspheres are widely used in site-specific drug delivery, gene therapy, and vaccine administration, improving immunogenicity, extending …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 251–268 Read article
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Artificial intelligence-integrated nanobiotechnology for precision medicine, smart diagnostics, and sustainable environmental applications
Abstract: Background: Nanobiotechnology integrates nanoscale materials with biological systems, enabling breakthroughs in drug delivery, biosensing, and environmental monitoring. However, the complexity of biological interactions and the vast parameter space of nano‑bio interfaces limit conventional design. Artificial intelligence (AI) offers powerful tools for modelling, predicting, and optimising these systems. Objective: This review provides a systematic, STM‑compliant overview of AI‑integrated nanobiotechnology across three domains: precision medicine (AI‑optimised nanocarriers, personalised therapeutics), smart diagnostics (AI‑powered …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 Read article
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A Comprehensive Review of Machine Learning and Explainable AI Techniques for Disease Prediction Systems
Abstract: Large amounts of diverse medical data have been produced because of the quick development of digital healthcare systems, offering substantial chances to use machine learning methods for clinical decision support and illness prediction. By identifying intricate patterns in clinical data, machine learning-based models have shown great promise in early disease detection, risk assessment, and personalised healthcare. However, issues with transparency, interpretability, and reliability have been brought up by the growing …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article